With the wider adoption of smartphones and Internet telephony there has been a corresponding increase in the volume of hands-free mobile telephony. By example smartphones utilize traditional cellular spectrum while laptop/notebook computers as well as smartphones often employ a WiFi or other local network as an on-ramp to the Internet for voice and/or video calls. Additionally, handsets can link via Bluetooth to a car radio to implement hands-free operation using the handset microphone and the radio speakers. Hands-free mobile telephony is expected to continue its increase in popularity.
Hardware manufacturers have typically implemented their hand-free devices with mass produced low cost loudspeakers. Qualitatively these are adequate in a limited range of linear operation, but the input signal to the loudspeaker is often outside that range and so that input signal is non-linearly transformed by the loudspeaker itself. This transformation proves problematic for conventional echo cancellation algorithms, which in practice now have to cope with the non-linear echo as well as the linear echo.
A transmitted signal which re-appears, with some delay in the transmitted or received signal, is with some qualification an acoustic echo to the originally transmitted signal. In the acoustic arts this is termed an echo signal, and a variety of software cancellation algorithms have been developed to eliminate it, often implemented in a device's voice engine. By example, a talker's voice representing what is termed a far-end signal is received at a handset receiver and output from the handset loudspeaker. This loudspeaker output is then picked up at the handset's microphone to be transmitted back to the original talker with some delay. The path directly between the loudspeaker and the microphone is termed the direct acoustic path but it is not the only one, there are further echo paths as the loudspeaker's output signal bounces around the handset's environment before being picked up at the microphone. Eliminating this echo signal while still retaining intended sounds picked up by the microphone in a full duplex operation (or full multiplex for conference calling) is the challenge of echo cancellation. Low cost loudspeakers with limited linear range result in a larger portion of the whole echo signal lying in the non-linear regime, and result in conventional echo cancellation algorithms designed primarily for a linear response to be less effective against the whole echo signal.
It is well known in the acoustic arts that a low cost loudspeaker for a mobile device can be modeled effectively by a memoryless non-linearity. One problem lies in identifying both the non-linear distortion and the linear acoustic echo path, and of course subsequent generation and cancellation of the acoustic echo to negate them. FIG. 1 illustrates this problem.
The far-end signal xt, which by example is input to FIG. 1 from a radio receiver Rx of the mobile telephony device of which FIG. 1 forms a part, undergoes an unknown non-linear transformation ƒ[ . . . ] due to the loudspeaker 102. The non-linearly mapped far-end signal ƒ[xt] then gets linearly convolved with the linear acoustic echo path wt to give the non-linear echo signal dt. The non-linear echo signal dt is superimposed by the near-end disturbance st=s′t+nt to give the signal yt which is picked up and output by the microphone 104. Here s′t and nt represent the near-end speech and observation noise, respectively. The twofold task then of the non-linear echo canceller 106 is to come up with an estimate ŵ1,t of the acoustic echo path wt as well as an estimate {circumflex over (ƒ)}[ . . . ] of the nonlinearity introduced in the system by the loudspeaker 104. The estimated echo signal {circumflex over (d)}t, which is generated using the estimates of the echo path and the nonlinear mapping, is then subtracted at 108 from the microphone signal to give the error signal et. The error signal et is then filtered by a Bayesian post-filter 112 to suppress the residual echo and is also taken as an input by the adaptive algorithm 110. The output ŝ′t of that post-filter 112 is transmitted to the far-end (by example, output from FIG. 1 to a transmitter Tx of the mobile telephony device of which FIG. 1 forms a part). In FIG. 1 the linear echo path estimate is denoted as ŵ1,t while the post-filter 112 operation is denoted as ŵ2,t. In the description below the estimated echo path estimate is simply given as ŵt and the post-filter is hereafter referenced as the Bayesian Post-filter, i.e., without a symbol.
The following prior art documents attempt to solve the problem of modeling the expansion coefficients of the nonlinear mapping, and the acoustic echo path as unknown deterministic parameters.                Learning of the non-linearity via a pre-processor followed by conventional adaptive filtering is detailed by A. Stenger and W. Kellermann in a paper entitled: RLS-ADAPTED POLYNOMIAL FOR NONLINEAR ACOUSTIC ECHO CANCELLING (Signal Processing, vol. 80, pp. 1747-1760, September 2000.)        A non-linear processor for selectively removing or reducing residual echo signals from an acoustic echo canceller associated with a telephony terminal is explored in U.S. Pat. No. 6,282,286 by Gordon Reesor et al.        Predistortion equalization is explored by K. Shi, X. Ma, and G. T. Zhou, in a paper entitled: NONLINEAR ACOUSTIC ECHO CANCELLATION USING A PSEUDO-COHERENCE FUNCTION (IEEE Trans. on Circuits and Systems I, vol. 55, no. 9, pp. 2639-2649, November 2008.).        A method and system for non-linear echo suppression is detailed at U.S. Pat. No. 7,672,445 by Ming Zhang et al. to include an echo canceller unit, a non-linear echo detection unit, and a non-linear echo suppression unit.        “Nonlinear acoustic echo cancellation using adaptive orthogonalized power filters”, ICASSP, 2005. By Fabian Kuech, Andreas Mitnacht and Walter Kellermann.        